HI,
GenAI Engineer (Only W2 no C2C)
Mandatory In-person interview in GA or NY
12+ Months (All Visa)
Role Overview
Candidates must have experience delivering enterprise AI solutions in production environments, NOT only POC or personal projects/Educational Projects .
We are seeking a Senior AI / GenAI Engineer with strong experience in machine learning, generative AI, and enterprise-scale AI platform development. The ideal candidate should have hands-on experience building production-grade AI systems, including Retrieval-Augmented Generation (RAG) platforms, vector search pipelines, autonomous AI agents, and scalable ML model deployment. The role requires expertise in Python-based ML development, LLM frameworks, vector databases, and AI orchestration frameworks such as LangChain, LangGraph, and Hugging Face.
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Provide this skill matrix for all profile submissions
GenAI Engineer- Skill/Competency Hands-on experience in years. Enter 0 if you have theoretical knowledge Rating (1-10)
10 Highest
Python
RAG, Vector DB, Chunking, Embedding
Data Pre-Processing
Prompt Engineering
GenAI Models Familiarity
Framework & Libraries - Lang Chain, Hugging Face, Lang graph similar framework build autonomous loop
Azure Cloud Computing/OpenAI services
API Integration and Development
Gen AI solution built for enterprise solutions (Not POC, Educational, Personal)
Mandatory In-person interview in GA or NY - Enter Yes to confirm.
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Required Skills
** Mandatory In-person interview in GA or NY
** Experience with enterprise level projects only - No college, Educational, POC Projects
Programming
- Strong Python development experience (7+ years).
Generative AI
- Hands-on experience with RAG, Vector DB, Embeddings and document chunking, Semantic search pipelines
AI Frameworks
- Experience with Lang Chain, Lang Graph, and Hugging Face.
Data Processing
- Experience with Pandas, NumPy, and data preprocessing pipelines.
Integration
- Experience deploying ML models as REST APIs and integrating AI with enterprise systems.
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Preferred Skills
- Experience with Natural Language Processing (NLP) and Deep Learning.
- Familiarity with Transformers and Large Language Models (LLMs).
- Experience with Cloud ML platforms such as Azure AI, AWS SageMaker etc.
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Nice to Have
- Experience building AI agents or autonomous systems.
- Knowledge of vector databases (Pinecone, Weaviate, Milvus, FAISS).
- Experience with MLOps practices, Docker, and Kubernetes.
Exposure to multimodal AI systems.
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